A systematic review on affective computing: Emotion models, databases, and recent advances
Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
EEG based emotion recognition: A tutorial and review
Emotion recognition technology through analyzing the EEG signal is currently an essential
concept in Artificial Intelligence and holds great potential in emotional health care, human …
concept in Artificial Intelligence and holds great potential in emotional health care, human …
[HTML][HTML] A systematic survey on multimodal emotion recognition using learning algorithms
Emotion recognition is the process to detect, evaluate, interpret, and respond to people's
emotional states and emotions, ranging from happiness to fear to humiliation. The COVID-19 …
emotional states and emotions, ranging from happiness to fear to humiliation. The COVID-19 …
Emotion recognition in EEG signals using deep learning methods: A review
Emotions are a critical aspect of daily life and serve a crucial role in human decision-making,
planning, reasoning, and other mental states. As a result, they are considered a significant …
planning, reasoning, and other mental states. As a result, they are considered a significant …
EEG-based emotion recognition using an end-to-end regional-asymmetric convolutional neural network
Emotion recognition based on electroencephalography (EEG) is of great important in the
field of Human–Computer Interaction (HCI), which has received extensive attention in recent …
field of Human–Computer Interaction (HCI), which has received extensive attention in recent …
Ferv39k: A large-scale multi-scene dataset for facial expression recognition in videos
Current benchmarks for facial expression recognition (FER) mainly focus on static images,
while there are limited datasets for FER in videos. It is still ambiguous to evaluate whether …
while there are limited datasets for FER in videos. It is still ambiguous to evaluate whether …
Au-assisted graph attention convolutional network for micro-expression recognition
Micro-expressions (MEs) are important clues for reflecting the real feelings of humans, and
micro-expression recognition (MER) can thus be applied in various real-world applications …
micro-expression recognition (MER) can thus be applied in various real-world applications …
EEG-based emotion recognition using 4D convolutional recurrent neural network
In this paper, we present a novel method, called four-dimensional convolutional recurrent
neural network, which integrating frequency, spatial and temporal information of …
neural network, which integrating frequency, spatial and temporal information of …
Differences first in asymmetric brain: A bi-hemisphere discrepancy convolutional neural network for EEG emotion recognition
Neuroscience research studies have shown that the left and right hemispheres of the human
brain response differently to the same or different emotions. Exploiting this difference in the …
brain response differently to the same or different emotions. Exploiting this difference in the …
Exploring temporal representations by leveraging attention-based bidirectional LSTM-RNNs for multi-modal emotion recognition
Emotional recognition contributes to automatically perceive the user's emotional response to
multimedia content through implicit annotation, which further benefits establishing effective …
multimedia content through implicit annotation, which further benefits establishing effective …